Adds a cookbook for File Search

[markmcd]

Covers all of the main features, including generation and CRUD for documents and file stores.

[review-notebook-app]

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[gemini-code-assist]

Summary of Changes

Hello @markmcd, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a new quickstart guide for the File Search API, designed to help users integrate hosted RAG systems with Gemini. The guide provides practical, step-by-step instructions and code examples for setting up file search stores, managing documents within them, and utilizing these stores to ground AI model generations with specific data, complete with metadata filtering capabilities.

Highlights

• New File Search Cookbook: A comprehensive cookbook has been added for the File Search API, demonstrating its capabilities for Retrieval-Augmented Generation (RAG) applications.
• Core Features Covered: The new cookbook covers essential features including the creation and management (CRUD) of File Search Stores and documents, uploading and importing files, and using these stores for content generation with accurate citations.
• Metadata Filtering: The cookbook illustrates how to leverage custom metadata for filtering search results, enabling more precise data retrieval during content generation.

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[gemini-code-assist]

Code Review

This pull request introduces a new cookbook for the File Search API, which is a great addition. The notebook is well-structured and covers the main features like creating stores, uploading documents, generating content with search, and managing resources. I've found a few issues, including one critical bug in the cleanup step and a couple of medium-severity points related to style guide adherence and notebook robustness. My detailed comments are below.

[markmcd]

PTAL!